The course of Data Visualization is a core course to B. Tech AI students at 4000 level. The course will introduce different data visualization principles and different types of data visualization. The course also complemented with mandatory laboratory work.

The course of social network analysis is an Elective course at 700 level offered for M. Tech, Ph.D. and Final Year B. Tech students. The course will introduce the domain of social network analysis and research problems therein. A student will understand the mathematical foundations required for addressing the problems related to social network analysis. Working with the data, algorithms and writing codes are inherent to the course syllabus. Python will be used for the programming language.

The course of Distributed Algorithms is an Elective course at 7000 level offered for M. Tech and B. Tech students. The course will introduce the concepts of distributed algorithms for real world problems. On completion of the course a student will be able to understand the most important basic results in the area of distributed algorithms, and interested students may begin independent research or take a more advanced course in distributed algorithms. The student will also able to implement distributed algorithms and understand & identify applications of distributed algorithms in real-world systems.